Mann‐Kendall (MK) trend test is frequently employed as the most familiar trend detection method. Its application requires serial independence of available hydrometeorological time series records. As suggested in the literature, the serial correlation effect can be removed from the given time series by using prewhitening, variance correction or overwhitening processes such as in the modified Mann‐Kendall (MMK) procedure. The PW process may cause some of the current trends to be removed along with the serial correlation. In this study, the MMK method is supported by Şen innovative trend analysis instead of Sen slope estimator (SSE). The MMK method is applied to monthly maximum temperatures of Oxford station in England, for which the data length is large and the moving trend slope values are calculated starting from 1854 for all durations between 1873 and 2017. The MMK_SSE and MMK_ITA methods yield significant increasing trends between 0.0037 and 0.0125°C/year annual slopes for January, March, May, July, August, September, October, November, December, but for February, there is not any significant trend. While MMK_SSE does not give any significant trend for April that has maximum positive kurtosis and skew, but MMK_ITA reflects an increasing trend of 0.0059°C per year.

As a natural disaster, drought has inverse effects on the agricultural and environmental sectors. Comprehensive drought evaluation is critical for integrated water resources management and drought monitoring. Drought is generally evaluated temporally and spatially without considering its trend, but in recent years, the study of drought trends has become common. However, in drought trend analyses, it is necessary to identify the frequency change of drought classification, along with the sub-trends and their magnitudes, which have been identified in this research with the combined frequency analysis and innovative trend analysis methodologies (F-ITA). Three different drought indices, the standardized precipitation index (SPI), Standardized precipitation evapotranspiration index (SPEI), and streamflow drought index (SDI), were calculated at different time scales at Florya Station, Istanbul, Türkiye, Durham Station in the United Kingdom, and Vargonas (Vargönäs) KRV Station in Sweden. The results showed that F-ITA improved the drought evaluation with a more detailed investigation of meteorological and hydrological drought trends on a microscale rather than stating a decrease or increase trend. There was no trend for SPI-3 and -6 F-ITA; for SPI-12 F-ITA, all drought classifications showed a monotonic increase trend. For example, for SPI-1 and SPEI-1 F-ITA, the abnormally dry classification showed minimal change with frequencies of 35%. The SPEI-12 F-ITA graph showed an increasing trend in all drought classifications. For SPEI-12, the frequency of exceptional drought (extremely dry) events increased from 0.11% (0.66%) to 1.21% (2.3%), while severe and moderate drought frequencies rose significantly from 3.73% to 4.61% and 7.46% to 11.4%, respectively. Finally, monotonic trend increases were noticed in the SDI at all time scales for all classifications. Graphical abstract